Purpose The current research aims to build base data for digital transformation(DX) of manufacturing companies and to develop guidelines to apply them. In particular, it intends to categorize DX technologies and identify the employees’ perception of DX. Based on that, it also aims to test a set of hypotheses about the relationship between absorptive capacity for DX technology and acceptance intention. Design/methodology/approach Based on the previous researches on digital transformation and technology absorption, a structural equation model was established with absorptive capacity introduced as an exogenous variable to the Technology Acceptance Model. DX technology under discussion includes Internet of Thing, Cloud Computing, Big Data, Artificial Intelligence, Virtual(Augmented) Reality, and 3D Printing. A set of 253 surveys were analyzed by utilizing the statistical programs o SPSS 23.0 and AMOS 23.0. Findings All the established hypotheses were supported. The effect of absorptive capacity on perceived usefulness (H1) and perceived easy of use (H2) was found positive. It was also found that perceived easy of use had a significant effect on perceived usefulness (H3) and acceptance intention (H5). The effect of perceived usefulness on acceptance intention (H4) was also positive. Research Implications or Originality The present research would be meaningful in that it presented empirical evidence for perception and implementation of digital transformation and that the concept of absorptive capacity was added to the TAM model. The results of analysis are expected to help direct further investigations into the issue.
Ⅰ. 서론
Ⅱ. 디지털 전환과 디지털기술
Ⅲ. 디지털 기술 수용에 관한 이론
Ⅳ. 연구방법
Ⅴ. 분석결과
Ⅵ. 결론 및 시사점
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